EDC-induced mechanisms of immunotoxicity: a systematic review.
Oscar Sabuz VidalDeepika DeepikaMarta SchuhmacherVikas KumarPublished in: Critical reviews in toxicology (2022)
Endocrine-disrupting chemicals (EDCs) refer to a group of chemicals that cause adverse effects in human health, impairing hormone production and regulation, resulting in alteration of homeostasis, reproductive, and developmental, and immune system impairments. The immunotoxicity of EDCs involves many mechanisms altering gene expression that depend on the activation of nuclear receptors such as the aryl hydrocarbon receptor (AHR), the estrogen receptor (ER), and the peroxisome proliferator-activated receptor (PPAR), which also results in skin and intestinal disorders, microbiota alterations and inflammatory diseases. This systematic review aims to review different mechanisms of immunotoxicity and immunomodulation of T cells, focusing on T regulatory (Treg) and Th17 subsets, B cells, and dendritic cells (DCs) caused by specific EDCs such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), bisphenols (BPs) and polyfluoroalkyl substances (PFASs). To achieve this objective, a systematic study was conducted searching various databases including PubMed and Scopus to find in-vitro , in-vivo , and biomonitoring studies that examine EDC-dependent mechanisms of immunotoxicity. While doing the systematic review, we found species- and cell-specific outcomes and a translational gap between in-vitro and in-vivo experiments. Finally, an adverse outcome pathway (AOP) framework is proposed, which explains mechanistically toxicity endpoints emerging from different EDCs having similar key events and can help to improve our understanding of EDCs mechanisms of immunotoxicity. In conclusion, this review provides insights into the mechanisms of immunotoxicity mediated by EDCs and will help to improve human health risk assessment.
Keyphrases
- systematic review
- gene expression
- estrogen receptor
- dendritic cells
- human health
- health risk assessment
- risk assessment
- meta analyses
- oxidative stress
- randomized controlled trial
- endothelial cells
- insulin resistance
- heavy metals
- climate change
- dna methylation
- stem cells
- emergency department
- machine learning
- single cell
- peripheral blood
- deep learning
- adverse drug